NDLI: The construction and validation of an RNA binding protein-related prognostic model for bladder cancer

Content Provider	Springer Nature : BioMed Central
Author	Chen, Fengxia Wang, Qingqing Zhou, Yunfeng
Abstract	Background RNA-binding proteins (RBPs) play crucial and multifaceted roles in post-transcriptional regulation. While RBPs dysregulation is involved in tumorigenesis and progression, little is known about the role of RBPs in bladder cancer (BLCA) prognosis. This study aimed to establish a prognostic model based on the prognosis-related RBPs to predict the survival of BLCA patients. Methods We downloaded BLCA RNA sequence data from The Cancer Genome Atlas (TCGA) database and identified RBPs differentially expressed between tumour and normal tissues. Then, functional enrichment analysis of these differentially expressed RBPs was conducted. Independent prognosis-associated RBPs were identified by univariable and multivariable Cox regression analyses to construct a risk score model. Subsequently, Kaplan–Meier and receiver operating characteristic curves were plotted to assess the performance of this prognostic model. Finally, a nomogram was established followed by the validation of its prognostic value and expression of the hub RBPs. Results The 385 differentially expressed RBPs were identified included 218 and 167 upregulated and downregulated RBPs, respectively. The eight independent prognosis-associated RBPs (EFTUD2, GEMIN7, OAS1, APOBEC3H, TRIM71, DARS2, YTHDC1, and RBMS3) were then used to construct a prognostic prediction model. An in-depth analysis showed lower overall survival (OS) in patients in the high-risk subgroup compared to that in patients in the low-risk subgroup according to the prognostic model. The area under the curve of the time-dependent receiver operator characteristic (ROC) curve were 0.795 and 0.669 for the TCGA training and test datasets, respectively, showing a moderate predictive discrimination of the prognostic model. A nomogram was established, which showed a favourable predictive value for the prognosis of BLCA. Conclusions We developed and validated the performance of a prognostic model for BLCA that might facilitate the development of new biomarkers for the prognostic assessment of BLCA patients.
Related Links	https://bmccancer.biomedcentral.com/counter/pdf/10.1186/s12885-021-07930-5.pdf
Ending Page	13
Page Count	13
Starting Page	1
File Format	HTM / HTML
ISSN	14712407
DOI	10.1186/s12885-021-07930-5
Journal	BMC Cancer
Issue Number	1
Volume Number	21
Language	English
Publisher	BioMed Central
Publisher Date	2021-03-08
Access Restriction	Open
Subject Keyword	Cancer Research Oncology Surgical Oncology Health Promotion and Disease Prevention Biomedicine Medicine Public Health Bladder cancer/BLCA TCGA RNA binding proteins Prognostic model Survival Medicine/Public Health
Content Type	Text
Resource Type	Article
Subject	Cancer Research Oncology Genetics
Journal Impact Factor	3.4/2023
5-Year Journal Impact Factor	3.8/2023

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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